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                <text>Faculty Publications</text>
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              <text>Rout, Amruta; Champatiray, Chiranjibi; Mahanta, Golak Bihari; Singh Sahni, Rajveer; Aggarwal, Tanishka; Maji, Kingshuk; Bahubalendruni, MVA Raju</text>
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              <text>Autonomous green vegetable growth monitoring via YOLOv9 and a vine robot with tracked mobility</text>
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              <text>01-01-2026</text>
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              <text>Expert Systems with Applications;Volume;321;Issue;;Article No.;132165;</text>
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              <text>&lt;a href="https://doi.org/10.1016/j.eswa.2026.132165" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.eswa.2026.132165&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105034884687?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105034884687?origin=resultslist&lt;/a&gt;</text>
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              <text>Rout A., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Champatiray C., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Mahanta G.B., Department of Mechatronics and Automation Engineering, National Institute of Technology Patna, Bihar, Patna, 800005, India; Singh Sahni R., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Aggarwal T., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Maji K., Department of Mechanical and Automobile Engineering, Christ University, Karnataka, Bengaluru, 560074, India; Bahubalendruni M.V.A.R., Industrial Robotics and Manufacturing Automation Laboratory, Department of Mechanical Engineering, National Institute of Technology Puducherry, Tamil Nadu, Karaikal, 609609, India</text>
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              <text>Urban agriculture is facing shrinking land while demand for food is increasing. The study introduces a vine-like, soft robot for non-destructive tracking of green vegetable development using a tracked mobile platform. Although an inbuilt camera and YOLOv9 object detector classify in real time and generate results in four size categories, very small, small, medium, and large, a flexible tube is everted into dense greenery through a pneumatic eversion process. Sensor fusion and hierarchical control are integrated to enable navigation through the complex canopies of crops with accurate control of pressure and direction, and steering. A field trial found 91% mAP detection accuracy at 38 FPS, accurate vine extension (1.2 m @ 4 cm/s), and stable locomotion over uneven terrain, resulting in constant coverage without harming the plants. The system provides a scalable solution for precision agriculture, enhancing crop inspection, disease diagnosis, and harvest planning through continuous data insights.  2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.</text>
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              <text>Growth tracking; Mobile inspection; Precision agriculture; Soft robotics; Vine robot; YOLOv9</text>
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              <text>Elsevier Ltd</text>
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              <text>ISSN: 9574174; CODEN: ESAPE</text>
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